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Assistant/Associate Professor - Data Science


University of North Texas, College of Information

Application Deadline: January 31, 2023


The College of Information - Department of Information Science at the University of North Texas (UNT) invites applications for a tenure-track Assistant/Associate Professor position to begin in Spring 2023. We are seeking exceptional candidates with interests in a wide range of topics within the theoretical, machine learning, and computational foundations of data science.


The candidate will teach, conduct research, and provide service in an academic position with emphasis in Data Science. The candidate must demonstrate a record of research accomplishments and have the ability to design and deliver courses in a variety of formats, including online and hybrid modalities in Data Science. The candidate is expected to teach Data Science undergraduate, graduate, and doctoral level courses and advise students in Data Science research. They are expected to work closely with doctoral students and to serve on dissertation committees. Exceptional candidates at the rank of Associate Professor will be considered. Senior candidates will be expected to have outstanding academic credentials that demonstrate their ability to conduct independent world-class research and attract external funding.


This is a nine month, full-time, tenure-track position. We seek candidates who will provide inspiration and leadership in research and teaching, who can leverage the strengths of the department’s dynamic faculty and programs, and who will build collaborative relationships in the University and profession.


The University of North Texas System and its component institutions are committed to equal opportunity and comply with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University of North Texas System and its component institutions do not discriminate on the basis of race, color, sex, sexual orientation, gender identity, gender expression, religion, national origin, age, disability, genetic information, or veteran status in its application and admission processes, educational programs and activities, and employment practices.


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